Top 10 Data Science Jobs that will be on high demand in 2022 [No. 4 will keep your mouth open}

Yes, there are numerous courses and books available out there on data science considering how immensely the world is dependent on data. However, what goes unnoticed is the fact that in addition to subject knowledge, there are quite a few skills that one needs to master in order to become a successful data scientist. With that being said, have a look at the top data science job skills that will be in high demand in 2022. Keep reading!

1. DataWrangling

Data science is nothing but making the best of data. This is where data-wrangling comes into play. Transforming data from one form to another is exactly what data wrangling is all about. This is extremely important as data science involves building models, exploring new features to build and perform deep dives, etc.

2. Statistics

One cannot deny the fact that data science is all about making the best of raw data. Simply put into words, it is concerned with extracting meaningful insights from unstructured data sets. There cannot be a better way to proceed with data sorting and analysis than by relying on statistics. Statistics helps in determining relationships among the data sets.

3. DataVisualization

Data science has a lot to do with analytical insights. How well a data scientist communicates analytical insights is directly proportional to meeting business objectives. Wondering how data visualization helps? Well, a data scientist with good visualisation skills stands the ability to present the data insights in a way that is well understood by everyone.

4. Building Pipelines

In data science, there will be instances where it is required to table or view a model or a data science project that does not exist. Thus, a successful data scientist is one who can write robust pipelines for your projects rather than relying on data analysts and/or data engineers. This saves time as well.

5. Critical Thinking

Critical thinking is something that talks about making well-informed, appropriate decisions based on data and facts. This is something that a data scientist aspirant needs to incorporate. Though this might appear challenging at first, one can surely master it over a period of time.

6. Programming

Data science has absolutely no meaning without programming. A successful data scientist is one who is comfortable with programming languages such as R, Python, Java, etc. This is because one can give instructions to the computer only in the form of programming. Thus, mastering this skill can never go wrong.

7. Problem Solving

Undoubtedly, a data scientist should be in a position to know how to solve problems. As a matter of fact, data science is associated with tons of problems – problems that need immediate solutions. To arrive at the solution, it is important to know where to start from. Therefore, a data scientist should know how to solve a problem and translate it into a durable and production-ready code.

8. Model Deployment

Model deployment, application of a model for prediction using new data, has a lot to do in the field of data science. Such a model helps in understanding the customers/target audience better thereby enabling the organization to work towards achieving those goals.

9. Communication

Data science is associated with transforming raw data into a form that is easily understood by everyone around to make better-informed decisions. This throws light on how crucial it is to have strong communication skills in place. With this skill, one can translate technical results to non-technical team members.

10. Teamwork

One cannot expect data scientists to work in isolation. A data scientist’s job role requires close interaction with other departments like finance, IT, operations, etc. This is why teamwork plays a pivotal role.

Credit: Analytics Insight

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